Professor Marius Portmann
Professor

Marius Portmann

Email: 
Phone: 
+61 7 336 51636

Background

Prof Portmann is the UQ-Cisco Chair of Network Security at the School of Electrical Engineering and Computer Science (EECS) at The University of Queensland (UQ).

He received his PhD in Electrical Engineering from the Swiss Federal Institute of Technology (ETH) in Zürich in 2003. His research interests include Computer Networks, Cybersecurity, IoT (Internet of Things) and applied AI.

Availability

Professor Marius Portmann is:
Available for supervision

Fields of research

Communications engineering Distributed computing and systems software Engineering

Qualifications

  • Masters (Coursework) of Science, Swiss Federal Institute of Technology ETH Zürich
  • Doctor of Philosophy, Swiss Federal Institute of Technology ETH Zürich

Research interests

  • Cyber Security

    Machine Learning based Intrusion Detection

  • Computer Networks

    IoT Networks, Software Defined Networking (SDN)

  • Blockchain Technology

Search Professor Marius Portmann’s works on UQ eSpace

190 works between 2002 and 2025
All (190) Book (1) Journal Article (62) Other Outputs (17) Conference Publication (103) Book Chapter (7)

1 - 20 of 190 works

2025

Journal Article

Crikey! Let’s keep it cozy like a joey in a pouch” Can humour or compassion encourage sustainable heater use at hotels?

Greene, Danyelle, Zinn, Anna K., Chen, Qingqing, Serati, Reza, Portmann, Marius and Dolnicar, Sara (2025). Crikey! Let’s keep it cozy like a joey in a pouch” Can humour or compassion encourage sustainable heater use at hotels?. Journal of Environmental Psychology, 107 102779, 1-14. doi: 10.1016/j.jenvp.2025.102779

Crikey! Let’s keep it cozy like a joey in a pouch” Can humour or compassion encourage sustainable heater use at hotels?

2025

Journal Article

An empirical evaluation of preprocessing methods for machine learning based network intrusion detection systems

Manocchio, Liam Daly, Layeghy, Siamak, Gallagher, Marcus and Portmann, Marius (2025). An empirical evaluation of preprocessing methods for machine learning based network intrusion detection systems. Engineering Applications of Artificial Intelligence, 158 111289, 1-16. doi: 10.1016/j.engappai.2025.111289

An empirical evaluation of preprocessing methods for machine learning based network intrusion detection systems

2025

Conference Publication

Quantised neural network NIDS on SmartNIC: balancing accuracy and efficiency in P4

Chen, Yaying, Layeghy, Siamak and Portmann, Marius (2025). Quantised neural network NIDS on SmartNIC: balancing accuracy and efficiency in P4. 50th Conference on Local Computer Networks (LCN), Sydney, NSW, Australia, 13-16 October 2025. Piscataway, NJ, United States: IEEE. doi: 10.1109/lcn65610.2025.11146316

Quantised neural network NIDS on SmartNIC: balancing accuracy and efficiency in P4

2025

Journal Article

Leveraging social norms and empathy to encourage sustainable air conditioning practices amongst hotel guests

Greene, Danyelle, Birenboim, Amit, Zinn, Anna K., Portmann, Marius, Pandey, Yash, Grün, Bettina and Dolnicar, Sara (2025). Leveraging social norms and empathy to encourage sustainable air conditioning practices amongst hotel guests. Journal of Environmental Psychology 102811, 102811. doi: 10.1016/j.jenvp.2025.102811

Leveraging social norms and empathy to encourage sustainable air conditioning practices amongst hotel guests

2025

Conference Publication

Multimodal LLMs for zero-shot intrusion detection using NetFlow visualisations

Luay, Majed, Layeghy, Siamak, Pandey, Yash, Kulatilleke, Gayan and Portmann, Marius (2025). Multimodal LLMs for zero-shot intrusion detection using NetFlow visualisations. 2025 IEEE 50th Conference on Local Computer Networks (LCN), Sydney, NSW Australia, 13-16 October 2025. Piscataway, NJ USA: Institute of Electrical and Electronics Engineers. doi: 10.1109/lcn65610.2025.11146352

Multimodal LLMs for zero-shot intrusion detection using NetFlow visualisations

2025

Journal Article

If you can’t measure it, you can’t improve it a comparison of technologies for capturing shower duration of hotel guests

Pandey, Yash, Chen, Qingqing, Portmann, Marius, Layeghy, Siamak and Dolnicar, Sara (2025). If you can’t measure it, you can’t improve it a comparison of technologies for capturing shower duration of hotel guests. Journal of Travel and Tourism Marketing, 42 (7), 983-993. doi: 10.1080/10548408.2025.2497959

If you can’t measure it, you can’t improve it a comparison of technologies for capturing shower duration of hotel guests

2025

Conference Publication

P4-NIDS: high-performance network monitoring and intrusion detection in P4

Chen, Yaying, Layeghy, Siamak, Manocchio, Liam Daly and Portmann, Marius (2025). P4-NIDS: high-performance network monitoring and intrusion detection in P4. 2025 Computing Conference, London, United Kingdom, 19-20 June 2025. Cham, Switzerland: Springer Cham. doi: 10.1007/978-3-031-92611-2_24

P4-NIDS: high-performance network monitoring and intrusion detection in P4

2025

Journal Article

EcoShower: estimating shower duration using non-intrusive multi-modal sensor data via LSTM and Gated Transformer models

Sablica, Lukas, Grün, Bettina, Layeghy, Siamak, Dolnicar, Sara and Portmann, Marius (2025). EcoShower: estimating shower duration using non-intrusive multi-modal sensor data via LSTM and Gated Transformer models. Expert Systems with Applications, 277 127202, 127202-277. doi: 10.1016/j.eswa.2025.127202

EcoShower: estimating shower duration using non-intrusive multi-modal sensor data via LSTM and Gated Transformer models

2025

Journal Article

P4-Secure: in-band DDoS detection in software defined networks

Daly Manocchio, Liam, Chen, Yaying, Layeghy, Siamak, Gwynne, David and Portmann, Marius (2025). P4-Secure: in-band DDoS detection in software defined networks. IEEE Transactions on Network and Service Management, 22 (2), 2120-2137. doi: 10.1109/tnsm.2025.3552844

P4-Secure: in-band DDoS detection in software defined networks

2025

Journal Article

Leveraging LSTM and reinforcement learning for adaptive sensing in CIoT nodes

Ghosh, Sushmita, Layeghy, Siamak, De, Swades, Chatterjee, Shouri and Portmann, Marius (2025). Leveraging LSTM and reinforcement learning for adaptive sensing in CIoT nodes. IEEE Transactions on Consumer Electronics, 71 (1), 178-188. doi: 10.1109/tce.2024.3516498

Leveraging LSTM and reinforcement learning for adaptive sensing in CIoT nodes

2025

Other Outputs

NF-CSE-CIC-IDS2018-v3

Luay, Majed, Layeghy, Siamak, Mohanad, Sarhan, Sayedehfaezeh, Hoseininoorbin, Moustafa, Nour and Portmann, Marius (2025). NF-CSE-CIC-IDS2018-v3. The University of Queensland. (Dataset) doi: 10.48610/ece9b83

NF-CSE-CIC-IDS2018-v3

2025

Other Outputs

NF-BoT-IoT-v3

Luay, Majed, Layeghy, Siamak, Mohanad, Sarhan, Sayedehfaezeh, Hoseininoorbin, Nour, Moustafa and Portmann, Marius (2025). NF-BoT-IoT-v3. The University of Queensland. (Dataset) doi: 10.48610/73c4ebc

NF-BoT-IoT-v3

2025

Other Outputs

NF-ToN-IoT-v3

Luay, Majed, Layeghy, Siamak, Mohanad, Sarhan, Sayedehfaezeh, Hoseininoorbin, Moustafa, Nour and Portmann, Marius (2025). NF-ToN-IoT-v3. The University of Queensland. (Dataset) doi: 10.48610/44d7c5e

NF-ToN-IoT-v3

2025

Other Outputs

NF-UNSW-NB15-v3

Luay, Majed, Layeghy, Siamak, Mohanad, Sarhan, Sayedehfaezeh, Hoseininoorbin, Moustafa, Nour and Portmann, Marius (2025). NF-UNSW-NB15-v3. The University of Queensland. (Dataset) doi: 10.48610/6e0eda1

NF-UNSW-NB15-v3

2025

Journal Article

SCGC : Self-supervised contrastive graph clustering

Kulatilleke, Gayan K., Portmann, Marius and Chandra, Shekhar S. (2025). SCGC : Self-supervised contrastive graph clustering. Neurocomputing, 611 128629, 128629. doi: 10.1016/j.neucom.2024.128629

SCGC : Self-supervised contrastive graph clustering

2024

Conference Publication

Towards Explainable Network Intrusion Detection using Large Language Models

Houssel, Paul R. B., Singh, Priyanka, Layeghy, Siamak and Portmann, Marius (2024). Towards Explainable Network Intrusion Detection using Large Language Models. 2024 IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT), Sharjah, United Arab Emirates, 16-19 December 2024. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/bdcat63179.2024.00021

Towards Explainable Network Intrusion Detection using Large Language Models

2024

Journal Article

FlowTransformer: A flexible python framework for flow-based network data analysis

Manocchio, Liam Daly, Layeghy, Siamak and Portmann, Marius (2024). FlowTransformer: A flexible python framework for flow-based network data analysis. Software Impacts, 22 100702, 100702. doi: 10.1016/j.simpa.2024.100702

FlowTransformer: A flexible python framework for flow-based network data analysis

2024

Journal Article

Does every hotel room need a minifridge? Empirical evidence from consumer self-reports and an automatic sensor-based system measuring electricity consumption and guest use

Dolnicar, Sara, Greene, Danyelle, Layeghy, Siamak and Portmann, Marius (2024). Does every hotel room need a minifridge? Empirical evidence from consumer self-reports and an automatic sensor-based system measuring electricity consumption and guest use. Annals of Tourism Research Empirical Insights, 5 (2) 100134. doi: 10.1016/j.annale.2024.100134

Does every hotel room need a minifridge? Empirical evidence from consumer self-reports and an automatic sensor-based system measuring electricity consumption and guest use

2024

Journal Article

A configurable anonymisation approach for network flow data: Balancing utility and privacy

Manocchio, Liam Daly, Layeghy, Siamak, Gwynne, David and Portmann, Marius (2024). A configurable anonymisation approach for network flow data: Balancing utility and privacy. Computers and Electrical Engineering, 118 109465, 1-16. doi: 10.1016/j.compeleceng.2024.109465

A configurable anonymisation approach for network flow data: Balancing utility and privacy

2024

Journal Article

FlowTransformer: A transformer framework for flow-based network intrusion detection systems

Manocchio, Liam Daly, Layeghy, Siamak, Lo, Wai Weng, Kulatilleke, Gayan K., Sarhan, Mohanad and Portmann, Marius (2024). FlowTransformer: A transformer framework for flow-based network intrusion detection systems. Expert Systems with Applications, 241 122564, 1-15. doi: 10.1016/j.eswa.2023.122564

FlowTransformer: A transformer framework for flow-based network intrusion detection systems

Current funding

  • 2025 - 2028
    Mechanisms of Behaviour Change Theory
    ARC Discovery Projects
    Open grant
  • 2024 - 2025
    Customer electricity usage segmentation based on smart meter data
    Energy Queensland Limited
    Open grant
  • 2021 - 2025
    Reducing plate waste in hotels - which interventions are most effective?
    ARC Linkage Projects
    Open grant

Past funding

  • 2022 - 2023
    Blockchain-based Event Ticketing System
    Innovation Connections
    Open grant
  • 2019
    Machine Learning for Automated Network Anomaly Detection, Cyber Security and Analysis - Phase II
    Innovation Connections
    Open grant
  • 2018 - 2019
    Machine Learning for Automated Network Anomaly detection and Analysis
    Innovation Connections
    Open grant
  • 2018
    Smart Lending
    Commonwealth Bank of Australia
    Open grant
  • 2017 - 2020
    Software Defined Networking for the Internet of Things
    Data 61 - University Collaboration Agreement (DUCA)
    Open grant
  • 2015 - 2016
    Test bed for wide-area software defined networking research (ARC LIEF project administered by The University of New South Wales)
    University of New South Wales
    Open grant
  • 2006 - 2008
    Generic Platform for Peer-to-peer Networks and Applications
    UQ New Staff Research Start-Up Fund
    Open grant

Availability

Professor Marius Portmann is:
Available for supervision

Before you email them, read our advice on how to contact a supervisor.

Available projects

  • Machine Learning for Computer Networking

    Harness Machine Learning and AI techniques, with a focus on Large Language Models, for the configuration and management of Computer Networks.

Supervision history

Current supervision

  • Doctor Philosophy

    Low-energy LoRaWAN-based automatic and continuous measurement of organisational environmental performance.

    Principal Advisor

    Other advisors: Dr Siamak Layeghy, Professor Sara Dolnicar

  • Doctor Philosophy

    Towards Practical Machine Learning Based Network Intrusion Detection

    Principal Advisor

    Other advisors: Associate Professor Marcus Gallagher, Dr Siamak Layeghy

  • Doctor Philosophy

    Exploring the Capabilities of LoRaWAN IoT Technology for Multisensor Data Collection and Analysis

    Principal Advisor

    Other advisors: Dr Siamak Layeghy, Professor Sara Dolnicar

  • Doctor Philosophy

    eXtended Management Network System (xNMS)

    Principal Advisor

    Other advisors: Dr Siamak Layeghy

  • Doctor Philosophy

    Machine Learning for Improving Services and Management of Software Defined Networks

    Associate Advisor

    Other advisors: Dr Siamak Layeghy

  • Doctor Philosophy

    Enhancing the Privacy-Preserving ML techniques with Functional Encryption approach

    Associate Advisor

    Other advisors: Dr Siamak Layeghy

  • Doctor Philosophy

    Multi-Receiver Passive Radar using WirelessLAN for Indoor Localisation

    Associate Advisor

    Other advisors: Associate Professor Konstanty Bialkowski

  • Doctor Philosophy

    Enhancing Cyberbullying Detection in Arabic Social Media through Explainable AI and Natural Language Processing: A Human-Centric Approach

    Associate Advisor

    Other advisors: Dr Siamak Layeghy

Completed supervision

Enquiries

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